PROJECT SUMMARY/ABSTRACT This is an NIMH R01 proposal entitled, ?Neuroprogression across the Psychosis Spectrum in the Early Course of Illness.? Neuroprogressive changes that occur through the early years of illness have been described using neurocognitive testing, PET, CT, fMRI, and post-mortem brain studies; however, these studies rely mainly on cross-sectional data, and longitudinal studies involving frequent measurements are rare, limiting our understanding of the actual timing and trajectories of these measures within this critical time period. The development and implementation of targeted and effective treatments is critically dependent on clear understanding of the timing and nature of disease progression in order to target processes amenable to intervention. Thus, there is an urgent need to carefully characterize neuroprogression in the early course of psychosis if we are to develop effective interventions to target areas of preserved functioning, potentially preventing further decline and chronic loss of functioning. This knowledge gap severely limits our ability to develop targeted treatments when they may be most effective, and to tailor treatment to patients' needs. The aim of the present proposal is the systematic, multimodal characterization of neuroprogression throughout the early course of illness in a cross-diagnostic sample of patients with psychosis using an accelerated longitudinal design. First, we will measure neurocognitive and neurobiological change over the first eight years of illness in order to characterize variability of timing and magnitude of neuroprogression across key measures. Second, we will assess the predictive utility of neuroprogressive trajectories on clinical and functional outcomes. We will also leverage the heterogeneity in baseline cognitive and brain measures to characterize patients by neuroprogressive profile and test whether baseline profiles offer improved prediction of clinical and functional course. The richness of these data will also position us to explore heterogeneity of neuroprogressive trajectories and their associations with clinical and functional outcomes. It has been argued that combining data from clinical, structural and functional imaging, and cognitive measures is superior to monomodal data in the prediction of course and outcome (6). Findings from this project will hasten identification of actionable treatment targets that are closely associated with clinical outcomes, and provide guidance for individualized treatment implementation during a critical period where early intervention strategies may be most effective. Notably, this proposal aims to build on the Human Connectome Project for Early Psychosis (U01MH109977, PI: Shenton) by utilizing the same high-quality methodology and adding longitudinal assessments to baseline data collection already underway, maximizing both the power of the present study and the utility of the HCP-EP data. The PI is an early stage investigator and K23 Awardee with a career focus on characterization of the nature and course of multidimensional symptom domains (e.g. cognition, reward processing), and targeted treatment approaches in psychosis.